Machine learning models of tobacco susceptibility and current use among adolescents from 97 countries in the Global Youth Tobacco Survey, 2013-2017

Exposure to pro-tobacco and anti-tobacco media messages and events and smoking behaviour among adolescents in Gambia

BACKGROUND

Despite the widespread prevalence of adolescent smoking in Gambia, a West African country, there is limited research exploring the relationships between exposure to pro-tobacco and anti-tobacco media messages and events and smoking behaviour among young people. This study investigates the interplay of these exposures and smoking behaviour among 11-17-year-old adolescents in Gambia.

METHODS

Secondary data analysis was conducted using the 2017 Gambia Global Youth and Tobacco Survey (GYTS), which included a total of 9,127 respondents. Descriptive and inferential analyses, including proportions, Pearson's chi-squared tests, and multivariable logistic regression models, were employed to estimate adjusted odds ratios (aOR) with 95% confidence intervals (CI).

RESULTS

The final model revealed significant associations between exposure to anti-tobacco media messages and events and smoking behaviour. Adolescents exposed to anti-tobacco media messages had a 29% increased odds of smoking (aOR 1.29,CI = 1.08,1.53) compared to those unexposed, while exposure to anti-tobacco media events showed a 31% increased odds (aOR 1.31,CI = 1.09,1.59) compared to those unexposed. Exposure to pro-tobacco messages, such as witnessing tobacco use on TV (aOR 1.41, CI = 1.17,1.69) and owning objects with tobacco brand logos (aOR 1.49,CI = 1.19,1.86), was associated with higher odds of smoking. Covariates, including sex, age, and exposure to smoking behaviour by significant others, also demonstrated associations with smoking behaviour. Notably, male respondents showed significantly higher odds of smoking (aOR = 4.01,CI = 3.28,4.89) compared to females. Respondents aged 15 years and older had increased odds of smoking (aOR = 1.47,CI = 1.22,1.76) compared to those below 15 years old. Those whose fathers smoke displayed higher odds of smoking (aOR = 1.35, CI = 1.04,1.76) compared to individuals with non-smoking parents. Additionally, those whose closest friends smoke showed remarkably higher odds of smoking (aOR = 2.87,CI = 2.37, 3.48) compared to those without such influence.

CONCLUSION

This study underscores the significant impact of exposure to both anti-tobacco and pro-tobacco media messages and events on smoking behaviour among adolescents in Gambia. However, pro-tobacco messages had a greater influence on smoking prevalence than anti-tobacco messages and events. Understanding these associations is crucial for devising effective public health interventions aimed at reducing tobacco use in this population.

Smoking Susceptibility and Trends Among Nonsmoking Adolescents: An International Study

OBJECTIVES

Smoking susceptibility is defined as a lack of firm decision against smoking, usually starts in the preparation and/or initiation stages of smoking behavior, and is a strong predictor of smoking experimentation during adolescence. However, the recent global prevalence and trends in smoking susceptibility among adolescents are not well documented. This study assessed global smoking susceptibility and secular trends among nonsmoking adolescents.

METHODS

Smoking susceptibility was analyzed using the most recent data from the Global Youth Tobacco Survey from 129 countries, where the data from each country were drawn from at least 1 survey conducted at any time between 1999 and 2020. Moreover, data from 82 countries were used to assess the average annual rate of change (AARC) in smoking susceptibility over time.

RESULTS

Smoking susceptibility among nonsmoking adolescents was 19.6%. A U-shaped relationship was observed between susceptibility and a country's economic level. Most countries showed no changes in susceptibility over time. Countries with a significant upward trend in susceptibility were primarily high-income and upper middle-income countries in the American region. At the World Health Organization regional level, susceptibility significantly decreased in the European region (AARC: -3.5%; 95% confidence interval, -5.8 to -0.8); however, it significantly increased in the American region (AARC: 2.2%; 95% confidence interval, 1.3-3.1).

CONCLUSIONS

Smoking susceptibility remains a serious public health challenge among adolescents worldwide. More public health policies are needed to reduce susceptibility and to control its upward trend in the American region and high-income countries.

Are the Relevant Risk Factors Being Adequately Captured in Empirical Studies of Smoking Initiation? A Machine Learning Analysis Based on the Population Assessment of Tobacco and Health Study

INTRODUCTION

Cigarette smoking continues to pose a threat to public health. Identifying individual risk factors for smoking initiation is essential to further mitigate this epidemic. To the best of our knowledge, no study today has used machine learning (ML) techniques to automatically uncover informative predictors of smoking onset among adults using the Population Assessment of Tobacco and Health (PATH) study.

AIMS AND METHODS

In this work, we employed random forest paired with Recursive Feature Elimination to identify relevant PATH variables that predict smoking initiation among adults who have never smoked at baseline between two consecutive PATH waves. We included all potentially informative baseline variables in wave 1 (wave 4) to predict past 30-day smoking status in wave 2 (wave 5). Using the first and most recent pairs of PATH waves was found sufficient to identify the key risk factors of smoking initiation and test their robustness over time. The eXtreme Gradient Boosting method was employed to test the quality of these selected variables.

RESULTS

As a result, classification models suggested about 60 informative PATH variables among many candidate variables in each baseline wave. With these selected predictors, the resulting models have a high discriminatory power with the area under the specificity-sensitivity curves of around 80%. We examined the chosen variables and discovered important features. Across the considered waves, two factors, (1) BMI, and (2) dental and oral health status, robustly appeared as important predictors of smoking initiation, besides other well-established predictors.

CONCLUSIONS

Our work demonstrates that ML methods are useful to predict smoking initiation with high accuracy, identifying novel smoking initiation predictors, and to enhance our understanding of tobacco use behaviors.

IMPLICATIONS

Understanding individual risk factors for smoking initiation is essential to prevent smoking initiation. With this methodology, a set of the most informative predictors of smoking onset in the PATH data were identified. Besides reconfirming well-known risk factors, the findings suggested additional predictors of smoking initiation that have been overlooked in previous work. More studies that focus on the newly discovered factors (BMI and dental and oral health status,) are needed to confirm their predictive power against the onset of smoking as well as determine the underlying mechanisms.

Smoking Among High School Students in Dili, Timor-Leste: Prevalence, Potential Determinants and Opportunities for Prevention and Control

Smoking initiation is concentrated among young people which strongly influences future smoking prevalence. This study aimed to investigate the prevalence of smoking and other tobacco product use and potential determinants in a cross-sectional survey of 1 121 students aged 13 to 15 years in Dili, Timor-Leste. The prevalence of ever using a tobacco product was 40.4% (males 55.5%; females 23.8%) and of current use was 32.2% (males 45.3%; females 17.9%). In a logistic multivariable regression, factors associated with current use of any tobacco product were being male, ≥US$1 weekly pocket money, parents smoking, exposure at home, and exposure in other locations. The findings suggest that reducing the very high use of tobacco among adolescents in Timor-Leste will require new policy measures, enhanced enforcement of current legislation as well as a focused commitment to targeted smoke-free education campaigns, and community-based health promotion to support parents to quit smoking and not smoke around children.

Susceptibility to smoking and determinants among never-smoking high school students in Thailand

INTRODUCTION

To prevent youth from becoming smokers, it is essential to understand factors contributing to them becoming susceptible to smoking. The aim of this study was thus to estimate the prevalence of smoking susceptibility among neversmoking youth in Thailand and to identify determinants associated with such behavior.

METHODS

Cross-sectional data for 4572 eighth-grade students (aged 13-15 years) from 120 secondary schools were obtained from a classroom-based survey using a self-administered questionnaire. Using data from never-smoking students (n=3180), simple and multiple logistic regression analyses were performed to identify factors associated with smoking susceptibility. Frequencies and proportions for descriptive statistics are reported along with adjusted odds ratios and 95% confidence intervals for logistic regression models.

RESULTS

A total of 16.4% of Thai never-smoking youth were susceptible to smoking. Several variables of interest were identified in multivariable analysis as significantly associated with increased susceptibility to smoking: being male (AOR=3.16; 95% CI: 25.4-3.92), having a positive attitude toward smoking - agreeing that smoking displays maturity (AOR=1.49; 95% CI: 1.07-2.09), the perception that smoking helps relieve stress (AOR=1.57; 95% CI: 1.14-2.15), the presence of current smoking peers (AOR=2.04; 95% CI: 1.57-2.66), exposure to secondhand smoking in public (AOR=1.51; 95% CI: 1.17-1.94), exposure to online cigarette and smoking-related advertising occasionally (AOR=1.98; 95% CI: 1.49-2.65), attendance at schools where there are sometimes anti-smoking education activities (AOR=1.57; 95% CI: 1.18-2.07); as well as exposure to anti-tobacco messages rarely (AOR=1.40; 95% CI: 1.05-1.87), occasionally (AOR=1.48; 95% CI: 1.12-1.96) and infrequently (AOR=1.41; 95% CI : 1.07-1.87).

CONCLUSIONS

Approximately one in six Thai never-smoking youth was found to be susceptible to smoking. Findings suggest it should be useful to supplement relevant tobacco prevention and control efforts by considering such interpersonal and socio-environmental determinants, among vulnerable people to smoke.

Association Between Place of Secondhand Smoke Exposure and Depression Among Nonsmoking Children and Adolescents: A Systematic Review

Secondhand smoke (SHS) exposure patterns of children and adolescents are different from those of adults because children and adolescents spend a majority of their time in the home and school. It was aimed to conduct a systematic review of the published literature regarding the association between depression and the place of SHS exposure among children and adolescents. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines, PubMed, ScienceDirect, and Cochrane Library databases were used for the literature review. The studies were screened and selected by two independent reviewers based on the inclusion criteria. All eight studies included in the systematic review measured SHS exposure in participants' own homes. Two studies measured SHS exposure at school and one study in cars. The majority of the studies showed a positive association between depression and SHS exposure in both private and public places among nonsmoking children and adolescents. Also, they concluded a dose-response relationship between SHS exposure and depression. Health practitioners would be encouraged to work with stakeholders to create smoke-free policies in both private and public places to avoid the adverse effects of SHS exposure.